Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_338327_weight_decay_0.02.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021450400352478027
Inter Cos: 0.11371058225631714
Norm Quadratic Average: 27.691619873046875
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023512111976742744
Inter Cos: 0.10041476786136627
Norm Quadratic Average: 33.10687255859375
Nearest Class Center Accuracy: 0.335125

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025697188451886177
Inter Cos: 0.09229281544685364
Norm Quadratic Average: 24.66983413696289
Nearest Class Center Accuracy: 0.3735

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022519253194332123
Inter Cos: 0.07282108068466187
Norm Quadratic Average: 26.310895919799805
Nearest Class Center Accuracy: 0.40625

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03172033280134201
Inter Cos: 0.08136370033025742
Norm Quadratic Average: 16.776193618774414
Nearest Class Center Accuracy: 0.43125

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031165339052677155
Inter Cos: 0.06898882985115051
Norm Quadratic Average: 17.070077896118164
Nearest Class Center Accuracy: 0.50275

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05648832395672798
Inter Cos: 0.08060787618160248
Norm Quadratic Average: 10.570037841796875
Nearest Class Center Accuracy: 0.7575

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.18403217196464539
Inter Cos: 0.10794041305780411
Norm Quadratic Average: 7.1308135986328125
Nearest Class Center Accuracy: 0.99975

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.80664825439453
Linear Weight Rank: 4031
Intra Cos: 0.6365851163864136
Inter Cos: 0.23023954033851624
Norm Quadratic Average: 56.69438934326172
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 15.734932899475098
Linear Weight Rank: 3670
Intra Cos: 0.9025147557258606
Inter Cos: 0.31709370017051697
Norm Quadratic Average: 28.936601638793945
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.6877589225769043
Linear Weight Rank: 10
Intra Cos: 0.9469034671783447
Inter Cos: 0.37077322602272034
Norm Quadratic Average: 18.70182228088379
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9605045318603516
Inter Cos: 0.45049434900283813
Norm Quadratic Average: 12.315201759338379
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.458673397064209
Accuracy: 0.585
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.2058970183134079, Weights: 0.02109798975288868
NC2 Equiangle: Features: 0.3701520284016927, Weights: 0.14945801628960503
NC3 Self-Duality: 0.3530570864677429
NC4 NCC Mismatch: 0.13049999999999995

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480459228157997
Inter Cos: 0.09352367371320724
Norm Quadratic Average: 27.53066635131836
Nearest Class Center Accuracy: 0.2895

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022734493017196655
Inter Cos: 0.0866379365324974
Norm Quadratic Average: 32.91649627685547
Nearest Class Center Accuracy: 0.3535

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02609352022409439
Inter Cos: 0.080331951379776
Norm Quadratic Average: 24.542469024658203
Nearest Class Center Accuracy: 0.4

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022671924903988838
Inter Cos: 0.06377726048231125
Norm Quadratic Average: 26.225683212280273
Nearest Class Center Accuracy: 0.4445

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02934013493359089
Inter Cos: 0.07110260426998138
Norm Quadratic Average: 16.72661590576172
Nearest Class Center Accuracy: 0.4595

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026632478460669518
Inter Cos: 0.05965139716863632
Norm Quadratic Average: 17.0338077545166
Nearest Class Center Accuracy: 0.4975

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03362414240837097
Inter Cos: 0.07214534282684326
Norm Quadratic Average: 10.526684761047363
Nearest Class Center Accuracy: 0.544

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05524776875972748
Inter Cos: 0.10269530862569809
Norm Quadratic Average: 6.955453395843506
Nearest Class Center Accuracy: 0.626

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.80664825439453
Linear Weight Rank: 4031
Intra Cos: 0.14905428886413574
Inter Cos: 0.22251974046230316
Norm Quadratic Average: 49.86937713623047
Nearest Class Center Accuracy: 0.606

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 15.734932899475098
Linear Weight Rank: 3670
Intra Cos: 0.23446932435035706
Inter Cos: 0.347761869430542
Norm Quadratic Average: 23.76630210876465
Nearest Class Center Accuracy: 0.5935

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.6877589225769043
Linear Weight Rank: 10
Intra Cos: 0.24690771102905273
Inter Cos: 0.40071365237236023
Norm Quadratic Average: 15.232725143432617
Nearest Class Center Accuracy: 0.589

Output Layer:
Intra Cos: 0.24276812374591827
Inter Cos: 0.44703200459480286
Norm Quadratic Average: 9.924760818481445
Nearest Class Center Accuracy: 0.5785

